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All Journal Jurnal Statistika dan Aplikasinya Jurnal Riset Statistika
Syahla Anisah
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

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Uji Dua Rata-Rata Waktu Belajar Mandiri Antara Mahasiswa Laki-Laki dan Perempuan Khalis Syahril Suryana; Syahla Anisah; Aceng Komarudin Mutaqin
Jurnal Riset Statistika Volume 4, No. 2, Desember 2024, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrs.v4i2.5002

Abstract

Abstract. In this report the author wants to discuss the two average tests regarding the length of independent study time (in hours) between male and female students of the 2019 Unisba statistics study program. To do this, a t test or independent sample t-test is needed. Because male and female students are independent sample group data. The conditions for being able to carry out a t test are that the data must be normally distributed and the two samples must have homogeneous variance. To be able to test whether the data is normally distributed or not, it is necessary to carry out a normality test using the Lilliefors test. And to test whether the two samples have homogeneous variances or not, a homogeneity of variance test was carried out using Fisher's test. After that, a t test can be carried out to find out whether the two averages are the same or different. Abstrak. Dalam laporan ini penulis ingin membahas tentang uji dua rata-rata mengenai lamanya waktu belajar mandiri (dalam jam) antara mahasiwa laki-laki dan perempuan prodi statstika 2019 Unisba. Untuk melakukan itu diperlukan uji t atau indpendent sample t-test. Karena mahasiswa laki-laki dan perempuan merupakan data kelompok sampel yang saling bebas. Syarat untuk dapat melakukan uji t yaitu data tersebut harus berdistribusi normal dan kedua sampel tersebut harus memiliki varians yang homogen. Untuk dapat menguji apakah data berdistribusi normal atau tidak, perlu dilakukan uji normalitas menggunakan uji Lilliefors. Dan untuk menguji apakah kedua sampel tersebut memiliki varians yang homogen atau tidak, dilakukan uji homogenitas varians dengan uji Fisher. Setelah itu, dapat dilakukan uji t untuk mengetahui apakah dua rata-rata tersebut sama atau berbeda.
MIXING DISTRIBUTION ANALYSIS OF MIXTURE POISSON DISTRIBUTION FOR THIRD PARTY LIABILITY INSURANCE CLAIM FREQUENCY DATA IN INDONESIA Aceng Komarudin Mutaqin; Syahla Anisah
Jurnal Statistika dan Aplikasinya Vol. 9 No. 1 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09101

Abstract

The Indonesian government plans to mandate Third Party Liability (TPL) insurance for all vehicle owners in 2025. However, statistical modeling of TPL claim frequency data in Indonesia has received limited attention in academic research. The mixture Poisson distribution can be considered as a distribution for Third Party Liability claim frequency data in Indonesia. This is because claim frequency data often experiences overdispersion. In this study, the mixing distribution of the mixture Poisson distribution for TPL claim frequency data in Indonesia will be analyzed using a bootstrap approach. The data used in this study is policyholder claim frequency data for comprehensive coverage of TPL for underwriting years 2015-2019 for vehicle categories 1, 2, 3 and 6 of PT. X in Indonesia. The results generally show that most distributions with more parameters have a larger p-value (more suitable for use as a mixing distribution for mixture Poisson distribution) than distributions with fewer parameters.
Co-Authors Aceng Komarudin Mutaqin Khalis Syahril Suryana